Protein phosphorylation is an important regulatory event in eukaryotic cells, guiding primary biological processes such as cell division, growth, migration, differentiation and intercellular communication (Hunter, 2000; Pawson and Scott, 2005). Protein phosphorylation plays an important role in normal organ development and function, such as liver, kidney, and other organismal tissue systems.
Several phosphorylation-related (PI3K and Akt signaling) liver phenotypes have been reported that are related to altered lipid and glucose metabolism through insulin control (Du et al., 2003; Stiles et al., 2004) and liver regeneration (ribosomal protein S6; Ruvinsky et al., 2005). Previously, only two studies have examined phosphorylation sites from primary liver tissue with observation of 26 sites (Jin et al., 2004) and 339 sites (Moser and White, 2006).
Proteins often contain multiple sites of phosphorylation, resulting in a high degree of versatility in functional regulation. Those sites can be modified independently or in a concerted manner to modulate a range of protein functions, from a single specific activity to higher order processes (Cohen, 2000; Roach, 1991; Yang, 2005). Each additional phosphorylation site attributed to a protein represents an exponential increase in the total number of possible molecular states and, therefore, in complexity and fine tuning potential for regulation.
Although the phosphoproteome of mammalian cells in culture has been extensively studied, acquired knowledge is limited to less than 8,000 known phosphorylation sites (Diella et al., 2004; Hornbeck et al., 2004).
A problem in conducting large-scale phosphorylation analysis concerns data processing and validation. There are three main issues. First, studies of posttranslational modifications cannot rely on redundant peptide identifications for correctness, i.e., multiple unique peptides assigned to the same protein. This results in the net confidence of identification resting solely on single peptide identifications.
Second, during protein fragmentation for amino acid sequence identification, phosphoserine- and phosphothreonine-containing peptides can produce fragmentation patterns that are often dominated by β-elimination products through loss of neutral phosphoric acid, which results in suppression of sequence-informative ions and consequently produces lower scores than unmodified peptides during database spectral matching.
Third, the presence of multiple serine, threonine and tyrosine candidate residues in a phosphopeptide can produce ambiguity when assigning the precise site of phosphorylation.
The prior art has previously resorted to tedious manual validation after database searching, which can be subjective and has become impractical as data sets have grown in size. There is a clear risk in supplying a phosphorylation site without also establishing an associated probability of correct site localization, in particular when attempting to associate a function for that particular modification.
There is a need for compositions and methods to obtain phosphorylated peptides and antibodies of these phosphorylated peptides.